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READ ME
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This repository contains some of the data and all of the scripts necessary for reproducing the results in the article "Inferring Individual Preferences from Group Decisions: Judicial Preference Variation and Aggregation on Collegial Courts" by Dominik Hangartner, Benjamin Lauderdale, and Judith Spirig, published in the British Journal of Political Science. 

Note that the data about the asylum appeals "AADecisions.csv" in the scripts "01_Descriptives.R" and "02_Run_Models.R" and the corresponding codebook are not included in the repository. To request the full dataset and the accompanying codebook, please contact the Swiss Federal Administrative Court, Deputy Executive Secretary, Postfach, 9023 St. Gallen, Switzerland; e-Mail: direction-taf@bvger.admin.ch. For 3,919 appeals, "AADecisions.csv" contains information on the appellant(s)'(s) country of origin, decision of appeal, binary appeal outcome, chair judge, second judge, third judge, appeal filing year, appeal decision year, whether the appeal was decided by a single judge, a single judge with the consent of a second judge, a three-judge panel, a five-judge panel, whether the case represents a unified appeal, and the legal issue of the appeal at the aggregate level. 

The repository contains the following files:

DOCUMENTATION
- Codebook.pdf		(description of variables contained in "aadata.Rda", "jdata.Rda", "materie_codes.Rda")


DATA FILES	
- aadata.Rda 		(contains information on whether or not appellant had a lawyer/paralegal for publicly available decisions)
- jdata.Rda		(contains data on judges, including identifiers, the political party they are affiliated with/a sympathiser of, the party colors and judges' years of experience)
- materie_codes.Rda	(overview of the code and description associated with legal issues)


R SCRIPTS
- 00_Models.R		(stan models)
- 01_Descriptives.R 	(reproduces descriptives in the paper)
- 02_RunModels.R	(script to run the stan models)
- 03_Results.R 		(reproduces all other numbers, tables and figures reported in the paper and some of the supplemental information appendix)



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Computing environment information:
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R version 4.4.2 (2024-10-31)
Platform: x86_64-apple-darwin20
Running under: macOS Sonoma 14.6.1

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] stargazer_5.2.3     xtable_1.8-4        rstan_2.32.6        StanHeaders_2.32.10 dplyr_1.1.4         

loaded via a namespace (and not attached):
 [1] vctrs_0.6.5        cli_3.6.3          rlang_1.1.4        generics_0.1.3     jsonlite_1.8.9    
 [6] RcppParallel_5.1.9 glue_1.8.0         colorspace_2.1-1   V8_6.0.0           gridExtra_2.3     
[11] pkgbuild_1.4.5     stats4_4.4.2       scales_1.3.0       grid_4.4.2         munsell_0.5.1     
[16] tibble_3.2.1       lifecycle_1.0.4    QuickJSR_1.5.1     inline_0.3.20      compiler_4.4.2    
[21] codetools_0.2-20   Rcpp_1.0.13-1      pkgconfig_2.0.3    rstudioapi_0.17.1  R6_2.5.1          
[26] tidyselect_1.2.1   curl_6.1.0         parallel_4.4.2     pillar_1.10.1      magrittr_2.0.3    
[31] loo_2.8.0          tools_4.4.2        gtable_0.3.6       matrixStats_1.5.0  ggplot2_3.5.1     